Abstract
Research in early childhood education has witnessed an increasing demand for high-quality, large-scale quantitative studies. This chapter discusses the contributions of quantitative research to early childhood education, summarises its defining features and addresses the strengths and limitations of different techniques and approaches. It provides an overview of new directions and state-of-the-art approaches in quantitative research, outlined under four key topic areas: identifying and understanding naturalistic groups (i.e., chi-square analysis, analysis of variance, cluster analysis), identifying mechanisms (i.e., correlation, regression analysis, structural equation modelling), identifying causation (i.e. randomised controlled trial, regression discontinuity) and identifying trajectories and patterns of change in individual learning, development and wellbeing (i.e. latent growth curve modelling, growth mixture modelling). Each section explains the selected research methods and illustrates these with recent examples drawn from early childhood quantitative research conducted in Australia, Canada, Germany, the United States and Chile.
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Harrison, L.J., Wang, C. (2018). Current Approaches in Quantitative Research in Early Childhood Education. In: Fleer, M., van Oers, B. (eds) International Handbook of Early Childhood Education. Springer International Handbooks of Education. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-0927-7_12
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